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Software Engineer Fraud Detection Jobs (NOW HIRING)

Rain

Machine Learning Engineer - Fraud Risk

New York, NY · On-site

$50K/yr

Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis * Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model ...

Fundrise

Senior Software Engineer

$125K - $165K/yr

They are seeking a Senior Software Engineer to evolve their investment screening and fraud ... fintech, fraud detection, risk, compliance, or a similarly regulated domain • Experience ...

DataVisor

Software Engineer

Mountain View, CA · On-site

Our award-winning software platform is powered by a team of world-class experts in big data ... As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters ...

DataVisor

Software Engineer

Mountain View, CA · On-site

Our award-winning software platform is powered by a team of world-class experts in big data ... As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters ...

DataVisor

Software Engineer

Mountain View, CA · On-site

Our award-winning software platform is powered by a team of world-class experts in big data ... As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters ...

Insight Global

Identity Fraud Analyst

Atlanta, GA · On-site

Document authentication software * Internal onboarding and case management systems Qualifications: * 2+ years of experience in fraud detection, risk analysis, or identity verification * Familiarity ...

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All JobsSoftware Engineer Fraud Detection Jobs

Software Engineer Fraud Detection information

See salary details

$24K

$104.9K

$189K

How much do software engineer fraud detection jobs pay per year?

As of Jun 7, 2026, the average yearly pay for software engineer fraud detection in the United States is $104,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $120,000.00 per year, depending on experience, location, and employer.

What does a Software Engineer in Fraud Detection do?

A Software Engineer in Fraud Detection designs and develops systems to identify and prevent fraudulent activities within digital platforms, such as banking or e-commerce environments. They build algorithms to analyze user behavior, detect anomalies, and flag suspicious transactions in real time. Their work often involves machine learning, big data analysis, and close collaboration with data scientists and security teams to continuously improve fraud detection accuracy. These engineers play a key role in protecting businesses and customers from financial loss and cybercrime.

What is the difference between Software Engineer Fraud Detection vs Data Scientist Fraud Detection?

AspectSoftware Engineer Fraud DetectionData Scientist Fraud Detection
Required CredentialsBachelor's in CS or related field, programming skillsBachelor's or higher in CS, Statistics, or Data Science
Work EnvironmentDevelops fraud detection systems, writes code, implements algorithmsAnalyzes data, builds models, interprets results
Employer & Industry UsageFinancial institutions, fintech, e-commerceFinancial services, tech companies, insurance
Common Search & ComparisonFocuses on software development for fraud detectionFocuses on data analysis and modeling for fraud detection

While both roles work in fraud detection, Software Engineer Fraud Detection primarily develops and maintains detection systems through coding, whereas Data Scientist Fraud Detection analyzes data and builds models to identify fraudulent activity. Both roles often collaborate but differ in their core focus and skill sets.

What are the key skills and qualifications needed to thrive as a Software Engineer in Fraud Detection, and why are they important?

To thrive as a Software Engineer in Fraud Detection, strong programming skills (such as Python, Java, or Scala), a solid understanding of algorithms, data structures, and experience with machine learning or statistical analysis are generally required, often supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), real-time analytics systems, and fraud detection tools or frameworks is typically expected. Analytical thinking, problem-solving abilities, and effective communication are key soft skills that differentiate top performers in this field. These skills are crucial for developing robust systems that can quickly identify and prevent fraudulent activities, protecting both users and organizations.

How does a Software Engineer in Fraud Detection typically collaborate with data scientists and analysts to identify fraudulent activity?

Software Engineers in Fraud Detection work closely with data scientists and analysts to build, refine, and deploy systems that detect and prevent fraud. While data scientists may develop models and identify patterns from large datasets, engineers are responsible for integrating these models into scalable, real-time systems within the company's technology stack. Regular communication and joint problem-solving are essential, as engineers must understand the logic behind models and analysts' findings to ensure accurate implementation and continuous improvement. This collaborative environment helps create robust fraud detection mechanisms that adapt to evolving threats.
More about Software Engineer Fraud Detection jobs
What cities are hiring for Software Engineer Fraud Detection jobs? Cities with the most Software Engineer Fraud Detection job openings:
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What job categories do people searching Software Engineer Fraud Detection jobs look for? The top searched job categories for Software Engineer Fraud Detection jobs are:
Software Engineer Fraud Detection jobs near you
Infographic showing various Software Engineer Fraud Detection job openings in the United States as of May 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $104,863 per year, or $50.4 per hour.

Lead Software Engineer (Python)

Prophecy Technologies

Boston, MA • On-site

Full-time

Posted yesterday

Job description

Role Summary
As a Lead Software Engineer (Python) at Trivelta, you will play a pivotal role in designing, developing, and scaling the platform's core backend infrastructure. This is a hands-on technical leadership position responsible for driving innovation, ensuring system performance, and maintaining high standards of security, compliance, and reliability.
You will collaborate closely with product, security, compliance, finance, and data analytics teams to build robust, scalable solutions in a highly regulated environment.
Key Responsibilities
Backend Architecture & Development
  • Architect and develop scalable, high-performance backend systems using Python.
  • Design and maintain robust APIs supporting mobile, web, and third-party integrations.
  • Drive best practices in backend design, code quality, and system reliability.

Performance, Security & Compliance
  • Optimize system performance, scalability, and availability.
  • Implement security best practices and ensure compliance with:
  • AML, KYC
  • Data privacy regulations
  • State-by-state sweepstakes regulations
  • Partner with compliance and security teams to meet regulatory standards.

Data & Analytics Infrastructure
  • Design and maintain data pipelines supporting:
  • Analytics and reporting
  • Fraud detection
  • Geolocation-based access controls
  • Regulatory and audit reporting

Technical Leadership
  • Lead and mentor engineers, promoting best practices and continuous learning.
  • Drive architectural decisions and long-term technical strategy.
  • Evaluate emerging technologies in fintech, gaming, and AI-based fraud detection.

Cross-Functional Collaboration
  • Work closely with product, finance, compliance, and support teams to translate business needs into technical solutions.
  • Ensure seamless system integration and operational efficiency.

Operational Excellence
  • Lead incident response for production outages or security events.
  • Implement proactive monitoring and alerting.
  • Perform root cause analysis and drive long-term corrective actions.

Required Skills & Qualifications
  • Proven experience designing and scaling high-performance backend systems.
  • Strong hands-on expertise in Python for backend development, automation, and data processing.
  • Experience building and maintaining RESTful APIs.
  • Strong knowledge of CI/CD pipelines and infrastructure automation.
  • Demonstrated ability to lead, mentor, and influence technical direction.
  • Experience working cross-functionally with product, finance, and compliance teams.
  • Solid understanding of:
  • System performance tuning
  • Security best practices
  • Regulatory compliance (AML, KYC, data privacy)

Preferred Qualifications
  • Experience with data pipelines, analytics platforms, and fraud detection systems.
  • Exposure to geolocation-based access controls.
  • Background in fintech, gaming, or regulated platforms.

Apply